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Background: Asthma and chronic obstructive pulmonary disease (COPD) are complex diseases, the definitions of which overlap. Objective: To investigate clustering of clinical/physiological features and readily available biomarkers in patients with physician-assigned diagnoses of asthma and/or COPD in the NOVEL observational longiTudinal studY (NOVELTY; NCT02760329). Methods: Two approaches were taken to variable selection using baseline data: approach A was data-driven, hypothesis-free and used the Pearson dissimilarity matrix; approach B used an unsupervised Random Forest guided by clinical input. Cluster analyses were conducted across 100 random resamples using partitioning around medoids, followed by consensus clustering. Results: Approach A included 3796 individuals (mean age, 59.5 years; 54% female); approach B included 2934 patients (mean age, 60.7 years; 53% female). Each identified 6 mathematically stable clusters, which had overlapping characteristics. Overall, 67% to 75% of patients with asthma were in 3 clusters, and approximately 90% of patients with COPD were in 3 clusters. Although traditional features such as allergies and current/ex-smoking (respectively) were higher in these clusters, there were differences between clusters and approaches in features such as sex, ethnicity, breathlessness, frequent productive cough, and blood cell counts. The strongest predictors of the approach A cluster membership were age, weight, childhood onset, prebronchodilator FEV1, duration of dust/fume exposure, and number of daily medications. Conclusions: Cluster analyses in patients from NOVELTY with asthma and/or COPD yielded identifiable clusters, with several discriminatory features that differed from conventional diagnostic characteristics. The overlap between clusters suggests that they do not reflect discrete underlying mechanisms and points to the need for identification of molecular endotypes and potential treatment targets across asthma and/or COPD.
Cluster Analyses From the Real-World NOVELTY Study: Six Clusters Across the Asthma-COPD Spectrum / Hughes, R.; Rapsomaniki, E.; Bansal, A. T.; Vestbo, J.; Price, D.; Agusti, A.; Beasley, R.; Fageras, M.; Alacqua, M.; Papi, A.; Mullerova, H.; Reddel, H. K.; Olmo, R. D.; Anderson, G.; Reddel, H.; Rabahi, M.; Mcivor, A.; Sadatsafavi, M.; Weinreich, U.; Burgel, P. -R.; Devouassoux, G.; Inoue, H.; Rendon, A.; van den Berge, M.; Garcia-Navarro, A. A.; Faner, R.; Olaguibel Rivera, J.; Janson, C.; Bilinska-Izydorczyk, M.; Fageras, M.; Fihn-Wikander, T.; Franzen, S.; Keen, C.; Ostridge, K.; Chalmers, J.; Harrison, T.; Pavord, I.; Azim, A.; Belton, L.; Ble, F. -X.; Erhard, C.; Gairy, K.; Lassi, G.; Scott, I. C.; Chipps, B.; Christenson, S.; Make, B.; Tomaszewski, E.; Benhabib, G.; Ruiz, X. B.; Lisanti, R. E.; Marino, G.; Mattarucco, W.; Nogueira, J.; Parody, M.; Pascale, P.; Rodriguez, P.; Silva, D.; Svetliza, G.; Victorio, C. F.; Rolon, R. W.; Yanez, A.; Baines, S.; Bowler, S.; Bremner, P.; Bull, S.; Carroll, P.; Chaalan, M.; Farah, C.; Hammerschlag, G.; Hancock, K.; Harrington, Z.; Katsoulotos, G.; Kim, J.; Langton, D.; Lee, D.; Peters, M.; Prassad, L.; Sajkov, D.; Santiago, F.; Simpson, F. G.; Tai, S.; Thomas, P.; Wark, P.; Cancado, J. E. D.; Cunha, T.; Lima, M.; Cardoso, A. P.; Fitzgerald, J. M.; Anees, S.; Bertley, J.; Bell, A.; Cheema, A.; Chouinard, G.; Csanadi, M.; Dhar, A.; Dhillon, R.; Kanawaty, D.; Kelly, A.; Killorn, W.; Landry, D.; Luton, R.; Mandhane, P.; Pek, B.; Petrella, R.; Stollery, D.; Wang, C.; Chen, M.; Chen, Y.; Gu, W.; Christopher Hui, K. M.; Li, M.; Li, S.; Lijun, M.; Qin, G.; Song, W.; Tan, W.; Tang, Y.; Wang, T.; Wen, F.; Wu, F.; Xiang, P.; Xiao, Z.; Xiong, S.; Yang, J.; Yang, J.; Zhang, C.; Zhang, M.; Zhang, P.; Zhang, W.; Zheng, X.; Zhu, D.; Bueno, C. M.; Grimaldos, F. B.; Arboleda, A. C.; de Salazar, D. M.; Bendstrup, E.; Hilberg, O.; Kjellerup, C.; Raherison, C.; Bonniaud, P.; Brun, O.; Chouaid, C.; Couturaud, F.; de Blic, J.; Debieuvre, D.; Delsart, D.; Demaegdt, A.; Demoly, P.; Deschildre, A.; Egron, C.; Falchero, L.; Goupil, F.; Kessler, R.; Le Roux, P.; Mabire, P.; Mahay, G.; Martinez, S.; Melloni, B.; Moreau, L.; Riviere, E.; Roux-Claude, P.; Soulier, M.; Vignal, G.; Yaici, A.; Bals, R.; Aries, S. P.; Beck, E.; Deimling, A.; Feimer, J.; Grimm-Sachs, V.; Groth, G.; Herth, F.; Hoheisel, G.; Kanniess, F.; Lienert, T.; Mronga, S.; Reinhardt, J.; Schlenska, C.; Stolpe, C.; Teber, I.; Timmermann, H.; Ulrich, T.; Velling, P.; Wehgartner-Winkler, S.; Welling, J.; Winkelmann, E. -J.; Barbetta, C.; Braido, F.; Cardaci, V.; Clini, E. M.; Costantino, M. T.; Cuttitta, G.; di Gioacchino, M.; Fois, A.; Foschino-Barbaro, M. P.; Gammeri, E.; Inchingolo, R.; Lavorini, F.; Molino, A.; Nucera, E.; Patella, V.; Pesci, A.; Ricciardolo, F.; Rogliani, P.; Sarzani, R.; Vancheri, C.; Vincenti, R.; Endo, T.; Fujita, M.; Hara, Y.; Horiguchi, T.; Hosoi, K.; Ide, Y.; Inomata, M.; Inoue, K.; Inoue, S.; Kato, M.; Kawasaki, M.; Kawayama, T.; Kita, T.; Kobayashi, K.; Koto, H.; Nishi, K.; Saito, J.; Shimizu, Y.; Shirai, T.; Sugihara, N.; Takahashi, K. -I.; Tashimo, H.; Tomii, K.; Yamada, T.; Yanai, M.; Rendon, A.; Cerino Javier, R.; Dominguez Peregrina, A.; Fernandez Corzo, M.; Montano Gonzalez, E.; Ramirez-Venegas, A.; Boersma, W.; Djamin, R. S.; Eijsvogel, M.; Franssen, F.; Goosens, M.; Graat-Verboom, L.; Veen, J. I.; Janssen, R.; Kuppens, K.; van de Ven, M.; Bakke, P.; Brunstad, O. P.; Einvik, G.; Hoines, K. J.; Khusrawi, A.; Oien, T.; Yoon, H. J.; Chang, Y. -S.; Cho, Y. J.; Hwang, Y. I.; Kim, W. J.; Koh, Y. -I.; Lee, B. -J.; Lee, K. -H.; Lee, S. -P.; Lee, Y. C.; Lim, S. Y.; Min, K. H.; Oh, Y. -M.; Park, C. -S.; Park, H. -S.; Park, H. -W.; Rhee, C. K.; Yoon, H. -K.; Garcia-Navarro, A. A.; Andujar, R.; Anoro, L.; Buendia Garcia, M.; Mozo, P. C.; Campos, S.; Casas Maldonado, F.; Castilla Martinez, M.; Cisneros Serrano, C.; Comeche Casanova, L.; Corbacho, D.; Campo Matias, F. D.; Echave-Sustaeta, J.; Corral, G. F.; Gamboa Setien, P.; Garcia Clemente, M.; Nunez, I. G.; Garcia Robaina, J.; Garcia Salmones, M.; Marin Trigo, J. M.; Fernandez, M. N.; Palomo, S. N.; Perez de Llano, L.; Pueyo Bastida, A.; Rano, A.; Rodriguez Gonzalez-Moro, J.; Reig, A. R.; Velasco Garrido, J.; Curiac, D.; Lif-Tiberg, C.; Luts, A.; Rahlen, L.; Rustscheff, S.; Adams, F.; Bradman, D.; Broughton, E.; Cosgrove, J.; Flood-Page, P.; Fuller, E.; Hartley, D.; Hattotuwa, K.; Jones, G.; Lewis, K.; Mcgarvey, L.; Morice, A.; Pandya, P.; Patel, M.; Roy, K.; Sathyamurthy, R.; Thiagarajan, S.; Turner, A.; Wedzicha, W.; Wilkinson, T.; Wilson, P.; Al-Asadi, L. A.; Anholm, J.; Averill, F.; Bansal, S.; Baptist, A.; Campbell, C.; Campos, M. A.; Crook, G.; Deleon, S.; Eid, A.; Epstein, E.; Fritz, S.; Harris, H.; Hewitt, M.; Holguin, F.; Hudes, G.; Jackson, R.; Kaufman, A.; Kaufman, D.; Klapholz, A.; Krishna, H.; Lee, D.; Lin, R.; Maselli-Caceres, D.; Mehta, V.; Moy, J. N.; Nwokoro, U.; Parikh, P.; Parikh, S.; Perrino, F.; Ruhlmann, J.; Sassoon, C.; Settipane, R. A.; Sousa, D.; Sriram, P.; Wachs, R.. - In: JOURNAL OF ALLERGY AND CLINICAL IMMUNOLOGY. IN PRACTICE. - ISSN 2213-2198. - 11:9(2023), pp. 2803-2811. [10.1016/j.jaip.2023.05.013]
Cluster Analyses From the Real-World NOVELTY Study: Six Clusters Across the Asthma-COPD Spectrum
Hughes R.;Rapsomaniki E.;Bansal A. T.;Vestbo J.;Price D.;Agusti A.;Beasley R.;Fageras M.;Alacqua M.;Papi A.;Mullerova H.;Reddel H. K.;Olmo R. D.;Anderson G.;Reddel H.;Rabahi M.;McIvor A.;Sadatsafavi M.;Weinreich U.;Burgel P. -R.;Devouassoux G.;Inoue H.;Rendon A.;van den Berge M.;Garcia-Navarro A. A.;Faner R.;Olaguibel Rivera J.;Janson C.;Bilinska-Izydorczyk M.;Fageras M.;Fihn-Wikander T.;Franzen S.;Keen C.;Ostridge K.;Chalmers J.;Harrison T.;Pavord I.;Azim A.;Belton L.;Ble F. -X.;Erhard C.;Gairy K.;Lassi G.;Scott I. C.;Chipps B.;Christenson S.;Make B.;Tomaszewski E.;Benhabib G.;Ruiz X. B.;Lisanti R. E.;Marino G.;Mattarucco W.;Nogueira J.;Parody M.;Pascale P.;Rodriguez P.;Silva D.;Svetliza G.;Victorio C. F.;Rolon R. W.;Yanez A.;Baines S.;Bowler S.;Bremner P.;Bull S.;Carroll P.;Chaalan M.;Farah C.;Hammerschlag G.;Hancock K.;Harrington Z.;Katsoulotos G.;Kim J.;Langton D.;Lee D.;Peters M.;Prassad L.;Sajkov D.;Santiago F.;Simpson F. G.;Tai S.;Thomas P.;Wark P.;Cancado J. E. D.;Cunha T.;Lima M.;Cardoso A. P.;FitzGerald J. M.;Anees S.;Bertley J.;Bell A.;Cheema A.;Chouinard G.;Csanadi M.;Dhar A.;Dhillon R.;Kanawaty D.;Kelly A.;Killorn W.;Landry D.;Luton R.;Mandhane P.;Pek B.;Petrella R.;Stollery D.;Wang C.;Chen M.;Chen Y.;Gu W.;Christopher Hui K. M.;Li M.;Li S.;Lijun M.;Qin G.;Song W.;Tan W.;Tang Y.;Wang T.;Wen F.;Wu F.;Xiang P.;Xiao Z.;Xiong S.;Yang J.;Yang J.;Zhang C.;Zhang M.;Zhang P.;Zhang W.;Zheng X.;Zhu D.;Bueno C. M.;Grimaldos F. B.;Arboleda A. C.;de Salazar D. M.;Bendstrup E.;Hilberg O.;Kjellerup C.;Raherison C.;Bonniaud P.;Brun O.;Chouaid C.;Couturaud F.;de Blic J.;Debieuvre D.;Delsart D.;Demaegdt A.;Demoly P.;Deschildre A.;Egron C.;Falchero L.;Goupil F.;Kessler R.;Le Roux P.;Mabire P.;Mahay G.;Martinez S.;Melloni B.;Moreau L.;Riviere E.;Roux-Claude P.;Soulier M.;Vignal G.;Yaici A.;Bals R.;Aries S. P.;Beck E.;Deimling A.;Feimer J.;Grimm-Sachs V.;Groth G.;Herth F.;Hoheisel G.;Kanniess F.;Lienert T.;Mronga S.;Reinhardt J.;Schlenska C.;Stolpe C.;Teber I.;Timmermann H.;Ulrich T.;Velling P.;Wehgartner-Winkler S.;Welling J.;Winkelmann E. -J.;Barbetta C.;Braido F.;Cardaci V.;Clini E. M.;Costantino M. T.;Cuttitta G.;di Gioacchino M.;Fois A.;Foschino-Barbaro M. P.;Gammeri E.;Inchingolo R.;Lavorini F.;Molino A.;Nucera E.;Patella V.;Pesci A.;Ricciardolo F.;Rogliani P.;Sarzani R.;Vancheri C.;Vincenti R.;Endo T.;Fujita M.;Hara Y.;Horiguchi T.;Hosoi K.;Ide Y.;Inomata M.;Inoue K.;Inoue S.;Kato M.;Kawasaki M.;Kawayama T.;Kita T.;Kobayashi K.;Koto H.;Nishi K.;Saito J.;Shimizu Y.;Shirai T.;Sugihara N.;Takahashi K. -I.;Tashimo H.;Tomii K.;Yamada T.;Yanai M.;Rendon A.;Cerino Javier R.;Dominguez Peregrina A.;Fernandez Corzo M.;Montano Gonzalez E.;Ramirez-Venegas A.;Boersma W.;Djamin R. S.;Eijsvogel M.;Franssen F.;Goosens M.;Graat-Verboom L.;Veen J. I.;Janssen R.;Kuppens K.;van de Ven M.;Bakke P.;Brunstad O. P.;Einvik G.;Hoines K. J.;Khusrawi A.;Oien T.;Yoon H. J.;Chang Y. -S.;Cho Y. J.;Hwang Y. I.;Kim W. J.;Koh Y. -I.;Lee B. -J.;Lee K. -H.;Lee S. -P.;Lee Y. C.;Lim S. Y.;Min K. H.;Oh Y. -M.;Park C. -S.;Park H. -S.;Park H. -W.;Rhee C. K.;Yoon H. -K.;Garcia-Navarro A. A.;Andujar R.;Anoro L.;Buendia Garcia M.;Mozo P. C.;Campos S.;Casas Maldonado F.;Castilla Martinez M.;Cisneros Serrano C.;Comeche Casanova L.;Corbacho D.;Campo Matias F. D.;Echave-Sustaeta J.;Corral G. F.;Gamboa Setien P.;Garcia Clemente M.;Nunez I. G.;Garcia Robaina J.;Garcia Salmones M.;Marin Trigo J. M.;Fernandez M. N.;Palomo S. N.;Perez de Llano L.;Pueyo Bastida A.;Rano A.;Rodriguez Gonzalez-Moro J.;Reig A. R.;Velasco Garrido J.;Curiac D.;Lif-Tiberg C.;Luts A.;Rahlen L.;Rustscheff S.;Adams F.;Bradman D.;Broughton E.;Cosgrove J.;Flood-Page P.;Fuller E.;Hartley D.;Hattotuwa K.;Jones G.;Lewis K.;McGarvey L.;Morice A.;Pandya P.;Patel M.;Roy K.;Sathyamurthy R.;Thiagarajan S.;Turner A.;Wedzicha W.;Wilkinson T.;Wilson P.;Al-Asadi L. A.;Anholm J.;Averill F.;Bansal S.;Baptist A.;Campbell C.;Campos M. A.;Crook G.;DeLeon S.;Eid A.;Epstein E.;Fritz S.;Harris H.;Hewitt M.;Holguin F.;Hudes G.;Jackson R.;Kaufman A.;Kaufman D.;Klapholz A.;Krishna H.;Lee D.;Lin R.;Maselli-Caceres D.;Mehta V.;Moy J. N.;Nwokoro U.;Parikh P.;Parikh S.;Perrino F.;Ruhlmann J.;Sassoon C.;Settipane R. A.;Sousa D.;Sriram P.;Wachs R.
2023
Abstract
Background: Asthma and chronic obstructive pulmonary disease (COPD) are complex diseases, the definitions of which overlap. Objective: To investigate clustering of clinical/physiological features and readily available biomarkers in patients with physician-assigned diagnoses of asthma and/or COPD in the NOVEL observational longiTudinal studY (NOVELTY; NCT02760329). Methods: Two approaches were taken to variable selection using baseline data: approach A was data-driven, hypothesis-free and used the Pearson dissimilarity matrix; approach B used an unsupervised Random Forest guided by clinical input. Cluster analyses were conducted across 100 random resamples using partitioning around medoids, followed by consensus clustering. Results: Approach A included 3796 individuals (mean age, 59.5 years; 54% female); approach B included 2934 patients (mean age, 60.7 years; 53% female). Each identified 6 mathematically stable clusters, which had overlapping characteristics. Overall, 67% to 75% of patients with asthma were in 3 clusters, and approximately 90% of patients with COPD were in 3 clusters. Although traditional features such as allergies and current/ex-smoking (respectively) were higher in these clusters, there were differences between clusters and approaches in features such as sex, ethnicity, breathlessness, frequent productive cough, and blood cell counts. The strongest predictors of the approach A cluster membership were age, weight, childhood onset, prebronchodilator FEV1, duration of dust/fume exposure, and number of daily medications. Conclusions: Cluster analyses in patients from NOVELTY with asthma and/or COPD yielded identifiable clusters, with several discriminatory features that differed from conventional diagnostic characteristics. The overlap between clusters suggests that they do not reflect discrete underlying mechanisms and points to the need for identification of molecular endotypes and potential treatment targets across asthma and/or COPD.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11588/990529
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simulazione ASN
Il report seguente simula gli indicatori relativi alla propria produzione scientifica in relazione alle soglie ASN 2023-2025 del proprio SC/SSD. Si ricorda che il superamento dei valori soglia (almeno 2 su 3) è requisito necessario ma non sufficiente al conseguimento dell'abilitazione. La simulazione si basa sui dati IRIS e sugli indicatori bibliometrici alla data indicata e non tiene conto di eventuali periodi di congedo obbligatorio, che in sede di domanda ASN danno diritto a incrementi percentuali dei valori. La simulazione può differire dall'esito di un’eventuale domanda ASN sia per errori di catalogazione e/o dati mancanti in IRIS, sia per la variabilità dei dati bibliometrici nel tempo. Si consideri che Anvur calcola i valori degli indicatori all'ultima data utile per la presentazione delle domande.
La presente simulazione è stata realizzata sulla base delle specifiche raccolte sul tavolo ER del Focus Group IRIS coordinato dall’Università di Modena e Reggio Emilia e delle regole riportate nel DM 589/2018 e allegata Tabella A. Cineca, l’Università di Modena e Reggio Emilia e il Focus Group IRIS non si assumono alcuna responsabilità in merito all’uso che il diretto interessato o terzi faranno della simulazione. Si specifica inoltre che la simulazione contiene calcoli effettuati con dati e algoritmi di pubblico dominio e deve quindi essere considerata come un mero ausilio al calcolo svolgibile manualmente o con strumenti equivalenti.